The current graph representation learning software ecosystem which allows academic research and industrial deployment extends open-source auto-differentiation libraries such as TensorFlow [1]}, PyTorch [2]}, MxNet [3]} and JAX [4]}, [5]}. Our work does the same as we build on the PyTorch Geometric ecosystem. We summarized the characteristics of these libraries in Table REF  which allows for comparing frameworks based on the backend, presence of supervised training functionalities, presence of temporal models and GPU support. Our proposed framework is the only one to date which allows the supervised training of temporal graph representation learning models with graphics card based acceleration.
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